python - pandas show multiple bar graphs on a chart -

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my data looks this:

term    date    change1 change2 aaa  2010-03-01   23.00   24.31 bbb  2010-03-01   25.00   0.00 ccc  2012-05-01   100.00  100.00

the date column can have repeated dates. want plot each term, change1 , change2 is. thinking have term x-axis , change1 , change2 share same y axis plotted bar charts side side. know how y axis part dont know how set x axis. each term somehow show date if possible otherwise not priority.

heres have:

fig = plt.figure() ax = fig.add_subplot(111) ax2 = ax.twinx() df.change1.plot(kind = 'bar', color = 'red', ax = ax , position = 1) df.change2.plot(kind = 'bar', color = 'blue', ax = ax2, position = 2) ax.set_ylabel= ('change1') ax2.set_ylabel=('change2') plt.show()

thanks,

one way make labels along x-axis terms set term index:

df = df.set_index(['term'])

for example,

import pandas pd import matplotlib.pyplot plt  df = pd.dataframe({'change1': [23.0, 25.0, 100.0],  'change2': [24.309999999999999, 0.0, 100.0],  'date': ['2010-03-01', '2010-03-01', '2012-05-01'],  'term': ['aaa', 'bbb', 'ccc']}) df = df.set_index(['term']) fig = plt.figure() ax = fig.add_subplot(111) ax2 = ax.twinx()  df['change1'].plot(kind='bar', color='red', ax=ax, position=0, width=0.25) df['change2'].plot(kind='bar', color='blue', ax=ax2, position=1, width=0.25) ax.set_ylabel = ('change1') ax2.set_ylabel = ('change2') plt.show()

enter image description here

or, instead of setting index, set xticklabels explicitly:

import pandas pd import matplotlib.pyplot plt  df = pd.dataframe({'change1': [23.0, 25.0, 100.0],  'change2': [24.309999999999999, 0.0, 100.0],  'date': ['2010-03-01', '2010-03-01', '2012-05-01'],  'term': ['aaa', 'bbb', 'ccc']})  fig = plt.figure() ax = fig.add_subplot(111) ax2 = ax.twinx()   df['change1'].plot(kind='bar', color='red', ax=ax, position=0, width=0.25) df['change2'].plot(kind='bar', color='blue', ax=ax2, position=1, width=0.25) ax.set_ylabel = 'change1' ax2.set_ylabel = 'change2' labels = ['{}\n{}'.format(date, term) date, term in zip(df['date'], df['term'])] ax.set_xticklabels(labels, minor=false) fig.autofmt_xdate()  plt.show()

enter image description here

per question in comments, create new plot each date, iterate on groups in df.groupby(['date']):

import pandas pd import matplotlib.pyplot plt  df = pd.dataframe({'change1': [23.0, 25.0, 100.0],  'change2': [24.309999999999999, 0.0, 100.0],  'date': ['2010-03-01', '2010-03-01', '2012-05-01'],  'term': ['aaa', 'bbb', 'ccc']})  groups = df.groupby(['date']) fig, axs = plt.subplots(nrows=groups.ngroups) groupi, ax in zip(groups,axs):     index, grp = groupi     ax2 = ax.twinx()     grp['change1'].plot(kind='bar', color='red', ax=ax, position=0, width=0.25)     grp['change2'].plot(kind='bar', color='blue', ax=ax2, position=1, width=0.25)     ax.set_ylabel = 'change1'     ax2.set_ylabel = 'change2'     ax.set_title(index)     ax.set_xticklabels(grp['term'].tolist(), minor=false, rotation=0) fig.tight_layout() plt.show()

enter image description here


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